T
Tata Consultancy Services
Python Data Scientist
Skills
Deep LearningPythonData ScienceData AnalysisMachine LearningAIAWSNLP / Natural Language ProcessingAzure
3 months ago
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Important information
Contract type:
Permanent
Location:
Hyderabad, Telangana, India
Work mode:
Hybrid
Published on:
11 August 2026
What they need
- Designed, developed, and deployed Machine Learning and Deep Learning models for industrial challenges involving large-scale numerical, categorical, and time series data, as well as images and videos.
- Extensive experience in Python programming for statistical analysis, custom algorithm development, and business insight generation using ML/DL models.
- Proficient in optimization techniques including Genetic Algorithms, Linear and Quadratic Programming, and others
- Skilled in comprehensive data workflows: collection, exploratory analytics, data cleansing, feature selection, and model validation.
- Experience in deploying AI/ML solutions using MLOPs on cloud platforms such as Azure and AWS.
- Solid knowledge of NLP, Large Language Models, Retrieval-Augmented Generation, and ML algorithms such as Decision Trees, Clustering, Support Vector Machines, Artificial Neural Networks, LSTM, CNN, and YOLO, with awareness of their practical advantages and limitations.
- Motivated by continuous learning and mastery of emerging technologies and methodologies in the fields of artificial intelligence and machine learning.
- Lead end to end design, development, and deployment of ML/DL solutions for complex business and industrial problems involving structured, time series, and unstructured data.
- Define modeling strategies and technical approaches, selecting appropriate ML, DL, Computer Vision, Optimization, and LLM techniques based on problem constraints and business impact.
- Oversee data science lifecycle governance, including data acquisition, exploratory analysis, feature engineering, model validation, and performance monitoring.
- Drive production grade deployment through MLOps, ensuring scalable, secure, and reliable model operations on cloud platforms such as Azure and AWS.
- Lead development of advanced analytics and optimization solutions, translating business objectives into prescriptive and decision support models.
- Provide technical leadership and mentoring to data science teams, establishing best practices in Python engineering, experimentation, and model reliability.
- Collaborate with stakeholders to translate business needs into AI solutions, clearly communicating assumptions, risks, outcomes, and measurable value.
- Continuously evaluate emerging AI/ML and LLM technologies, driving innovation, POCs, and capability building aligned with organizational strategy.
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